code: def _input_mappings(self, batch_data, train):
      default_input_map = super(CDL, self)._input_mappings(
          batch_data=batch_data, train=train
      )
      if train:
          default_input_map[
              self._get_input("item_feature")
          ] = self._item_f[batch_data["item_id_input"]]
      else:
          default_input_map[
              self._get_input("item_id", train=False)
          ] = batch_data["item_id_input"]
          default_input_map[
              self._get_input("item_feature", train=False)
          ] = self._item_f[batch_data["item_id_input"]]
      return default_input_map
  
file_path: openrec/openrec/tf1/legacy/recommenders/cdl.py
imports: from openrec.tf1.legacy.recommenders import PMF
  from openrec.tf1.legacy.modules.extractions import SDAE
  from openrec.tf1.legacy.modules.fusions import Average
label_desc: Use image node_id 3 for calling the CDL obj's underlying member method code with example usage: obj._input_mappings(batch_data, train) and returns: default_input_map